SmolLM3-3B, OpenVINO INT4 channel-wise (NPU)
HuggingFaceTB/SmolLM3-3B at commit
a07cc9a04f16550a088caea529712d1d335b0ac1, exported to OpenVINO IR with weights in
symmetric, channel-wise INT4. Channel-wise (--group-size -1) is the layout the Intel NPU
compiles quickly; a group-wise INT4 export of a similar model was still compiling after ten
minutes.
Made for vinoWhisper, which uses it on the NPU to clean up dictation, and pins this repo by commit and per-file sha256.
How it was made
optimum-cli export openvino --model HuggingFaceTB/SmolLM3-3B \
--task text-generation-with-past --weight-format int4 --sym --ratio 1.0 --group-size -1 out/
From a local download of the commit above. OpenVINO 2026.4.1, openvino-tokenizers 2026.4.1.0, optimum-intel 2.2.0, optimum 2.3.0, nncf 3.4.0, transformers 5.3.0, torch 2.14.1. Nothing else was changed.
Measured (2026-10-27, Intel Core Ultra NPU, 16 TOPS, OpenVINO GenAI 2026.4.1)
LLMPipeline(..., "NPU", MAX_PROMPT_LEN=3072, MIN_RESPONSE_LEN=512), greedy, /no_think:
| Decode | 18-22 tokens/s |
| First token, 550 / 1450 / 2800-token prompt | 1.5 / 3.1 / 5.1 s |
| Peak RSS | 3.1 GB |
| First load (compile) | ~24 s, then cached |
One laptop, n=1 per figure. For summaries, set repetition_penalty=1.1: with greedy
decoding and no penalty, one long summary looped.
Licence
Apache 2.0, the same as the base model.